CN109034419A - Using the method for big data theoretical optimization nuclear power plant inservice inspection project and frequency - Google Patents
Using the method for big data theoretical optimization nuclear power plant inservice inspection project and frequency Download PDFInfo
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- 238000007689 inspection Methods 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000005457 optimization Methods 0.000 title claims abstract description 23
- 238000012423 maintenance Methods 0.000 claims abstract description 19
- 238000004458 analytical method Methods 0.000 claims abstract description 14
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 238000003860 storage Methods 0.000 claims abstract description 4
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 230000008439 repair process Effects 0.000 claims description 4
- 230000001419 dependent effect Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 238000000611 regression analysis Methods 0.000 claims description 3
- 230000004888 barrier function Effects 0.000 claims description 2
- 238000004513 sizing Methods 0.000 claims description 2
- 238000007405 data analysis Methods 0.000 description 3
- 238000007418 data mining Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000000945 filler Substances 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 238000012856 packing Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000005086 pumping Methods 0.000 description 1
- 230000000246 remedial effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract
The invention belongs to nuclear power plants to run technical field, be related to the method using big data theoretical optimization nuclear power plant inservice inspection project and frequency.The method in turn includes the following steps: (1) big data is collected；(2) foundation of database, the storage and extraction of data；(3) pretreatment of data；(4) modeling and analysis of data；(5) optimize inservice inspection.Utilize the method for the invention using big data theoretical optimization nuclear power plant inservice inspection project and frequency, the analysis of the mass data accumulated to nuclear power plant's inservice inspection and maintenance aspect can be passed through, it was found that rule, to preferably optimize project, method and the frequency of inservice inspection.
Description
Technical field
The invention belongs to nuclear power plants to run technical field, be related to using big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency.
Background technique
Inservice inspection is that have within nuclear power plant's operation phase in longevity to what 1-3 grades of systems of nuclear safety, component and its support were carried out
The periodic inspection of plan to find newly generated defect in time and (or) to track the extension of known defect, and judges that they are right
Whether nuclear power plant's operation can receive, or whether it is necessary to adopt remedial measures.
At present there are mainly two types of the strategy/specification for determining nuclear power plant's inservice inspection project, i.e. France RSE-M specification uses
Destroy the Sampling Strategies of guiding strategy and American ASME use.
RSEM is based on determining discussing safety analysis as a result, careful define the system equipment that need to be checked, check point, connect
Nearly mode, inspection method and inspection frequency.ASME first classifies checked object, then for each inspection, ASME
Output detection method, acceptance criteria, detection range and frequency are given in a tabular form.For a certain specific nuclear power station, built by ASME
Vertical unit inservice inspection outline needs the actual conditions for the heap-type to carry out combing refinement by equipment.Such as ASME provides core
1 grade of dissimilar metal (B-F) type pipeline-weld of safety 100% must do inservice inspection, 1 grade of same metal pipeline-weld pumping of nuclear safety
25% inspection is taken, 2 grades of pipeline-welds of nuclear safety extract 7.5%.
Above two tactful method in other words does not consider the reliability of influence and equipment of the cracking effects to safety, causes
The project and frequency of inspection are higher, and there are certain optimization spaces.
Big data has obtained more and more applications in all trades and professions in recent years, can obtain by the analysis to mass data
In to these data information and connection, to the original design of Optimal improvements or create new design.Nuclear power plant is in-service
A large amount of data are had accumulated in terms of inspection and maintenance, by carrying out mining analysis, discovery rule to these data, can be optimized in-service
Project, method and the frequency of inspection.
Summary of the invention
The object of the present invention is to provide application big data theoretical optimization nuclear power plant inservice inspection project and frequency method, with
The analysis of the mass data accumulated to nuclear power plant's inservice inspection and maintenance aspect, discovery rule, thus preferably excellent can be passed through
Change project, method and the frequency of inservice inspection.
In order to achieve this, the present invention is provided to exist using big data theoretical optimization nuclear power plant in the embodiment on basis
The method for using as a servant inspection item and frequency, the method in turn include the following steps:
(1) big data is collected；
(2) foundation of database, the storage and extraction of data；
(3) pretreatment of data；
(4) modeling and analysis of data；
(5) optimize inservice inspection.
In terms of big data application is introduced nuclear power plant's inservice inspection by the present invention.Numerous nuclear power plant's operations and maintenance are collected first
Data, especially nuclear power plant's preventative maintenance, running equipment failure and overhaul maintenance etc. data, he establishes the fortune of important equipment to safety
Row maintenance database, then carries out data mining and analysis based on the database, finally using current inservice inspection outline as base
Plinth, optimization inservice inspection project, method and frequency.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency, wherein in step (1), the data of collection include device identification data, sizing of equipment data, device type number
According to, inservice inspection data, historical failure data, maintenance experience data, local environment data.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency, wherein in step (1), the data of collection include equipment unique encodings, device name, place system designator code,
Functions of the equipments, security level, specification grade, seismic behavior, quality guarantee grade, position, manufacturing firm, inservice inspection method,
Inservice inspection frequency, acceptance criteria, last inservice inspection result, requirement for major repairs, last overhaul result, preventative maintenance are wanted
It asks, pressure, the temperature, load information that last time preventative maintenance result, operation troubles and equipment are born, including equipment institute
Locate some device-dependent information including the pressure, temperature, humidity atmosphere of position.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency, wherein in step (1), the data of the most of nuclear power plant in the whole nation is collected, can also be received in conditional situation
Collect the data of external nuclear power plant.Big data is primarily characterized in the vast of primary data amount, therefore not only to collect each core
The current data of power plant should also collect data all since running from nuclear power plant as far as possible.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency, wherein in step (2), based on current inservice inspection outline, in conjunction with nuclear power plant's preventative maintenance, run
Equipment fault and overhaul mantenance data, establish inservice inspection integrated database.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency, wherein in step (2), sort merge is carried out to tables of data different in database is established, establishes multilist connection
System.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
Duplicate, vacancy or abnormal data are handled wherein in step (3) with the method for frequency, is allowed to meet and want
It asks.But after the amount of data is especially big, accuracy can be reduced, and it is particularly accurate for neither requiring every data all.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
The equipment for failure once occurred is retrieved in the database, using regression analysis, is looked for wherein in step (4) with the method for frequency
It has the case where feature and inservice inspection for being easy to appear failure, and by data mining, finds out the data for the equipment that breaks down
With the correlation of other data.The correlation is not necessarily causality, but a certain equipment is still caused easily to break down, because
This its be the core of big data analysis.
In a kind of more preferred embodiment, the present invention, which provides, applies the inservice inspection of big data theoretical optimization nuclear power plant
The method of project and frequency wherein in step (4), analyzes data in combination with equipment dependability database and nuclear power plant PSA,
More effectively to find the problem.
In a kind of more preferred embodiment, the present invention, which provides, applies the inservice inspection of big data theoretical optimization nuclear power plant
The method of project and frequency, wherein increasing in step (5) to the equipment with identical data for the data for the equipment that breaks down
Add the project and frequency of inservice inspection, to avoid device fails.
In a preferred embodiment, the present invention, which provides, applies big data theoretical optimization nuclear power plant inservice inspection project
With the method for frequency, wherein in step (5), according to the analysis of step (4) as a result, it is more for inservice inspection and be less prone to therefore
The equipment of barrier, it is proposed that reduce inservice inspection；Less for inservice inspection and failure frequent occurrence equipment, it is proposed that increase in-service inspection
It looks into.
The beneficial effects of the present invention are utilize application big data theoretical optimization nuclear power plant inservice inspection project of the invention
With the method for frequency, rule can be found by the analysis of the mass data accumulated to nuclear power plant's inservice inspection and maintenance aspect,
To preferably optimize project, method and the frequency of inservice inspection.
Specific embodiment
A specific embodiment of the invention is further illustrated below.
Illustratively the method for the invention using big data theoretical optimization nuclear power plant inservice inspection project and frequency includes
Following steps.
(1) big data is collected
Collect data content at least need include equipment unique encodings, device name, place system designator code, functions of the equipments,
Security level, specification grade, seismic behavior, quality guarantee grade, position, manufacturing firm, inservice inspection method, inservice inspection frequency
Rate, acceptance criteria, last inservice inspection result, requirement for major repairs, last overhaul result, preventative maintenance require, are last
Pressure, the temperature, load information of preventative maintenance result, operation troubles and equipment receiving, the pressure including equipment present position
Some device-dependent information including power, temperature, humidity atmosphere etc..The data volume of one nuclear power plant is too small, insufficient
To embody statistics rule, the data of national most of nuclear power plant are collected.
(2) foundation of database, the storage and extraction of data
Based on current inservice inspection outline, tieed up in conjunction with nuclear power plant's preventative maintenance, running equipment failure and overhaul
It the data such as repairs, establishes inservice inspection integrated database.Sort merge is carried out to tables of data different in database is established, is established more
Table connection.
(3) pretreatment of data
Some duplicate, vacancy or abnormal data are handled, are allowed to meet the requirements.
(4) modeling and analysis of data
The equipment for failure once occurred is retrieved in the database, using regression analysis, finds out the spy for being easy to appear failure
The case where sign and inservice inspection, and by data mining, find out the data for the equipment that breaks down and the correlation of other data.
This step analyzes data in combination with equipment dependability database and nuclear power plant PSA simultaneously, can more effectively find to ask in this way
Topic.
(5) optimize inservice inspection
According to the analysis of step (4) as a result, more for inservice inspection and be not easy the equipment to break down, it is proposed that reduce and exist
Labour checks；Less for inservice inspection and failure frequent occurrence equipment, it is proposed that increase inservice inspection.Especially for generation event
Hinder the data of equipment, the project and frequency to increase inservice inspection to the equipment with identical data are kept away to find defect early
Exempt from device fails.
The method of the invention using big data theoretical optimization nuclear power plant inservice inspection project and frequency of above-mentioned example
Applicating example it is as follows.
(1) information of nuclear power plant's all devices is collected.
(2) information being collected into is established into table, is stored in database profession according to the requirement of database.
(3) some duplicate, vacancy or abnormal data are handled, is allowed to meet the requirements.
(4) data analysis is carried out to the equipment to break down, it is found that the time of the valve rod leakage of certain nuclear power plant concentrates
Occur in annual June.Therefore, should reinforce checking before annual June, to avoid the generation of valve leak.
(5) further analysis shows, this Ge Yue nuclear power plant location ambient humidity is especially big, if former valve stem packing
Weathered, former valve rod easily damages at high humidity, and valve stem packing is caused to leak.In this way, test valve can be arranged in May
Door filler, replaces weathered filler.Although this increases inspection, valve leak is avoided, reduces unplanned shutdown,
Nuclear power plant is safer and economy is also higher.
In examples detailed above, after the data of collection are enough, it is easier to find the correlativity between some parameters, very
To being no causal correlativity.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.If in this way, belonging to the model of the claims in the present invention and its equivalent technology to these modifications and changes of the present invention
Within enclosing, then the present invention is also intended to include these modifications and variations.Above embodiment only illustrates to of the invention
Bright, the present invention can also be implemented with other ad hoc fashions or other particular forms, without departing from the gist of the invention or originally
Matter feature.Therefore, the embodiment of description is regarded as illustrative and non-limiting in any way.Model of the invention
Enclosing should be illustrated by appended claims, and any variation equivalent with the intention and range of claim should also be included in the present invention
In the range of.
Claims (10)
1. the method for application big data theoretical optimization nuclear power plant inservice inspection project and frequency, which is characterized in that the method
It in turn includes the following steps:
(1) big data is collected；
(2) foundation of database, the storage and extraction of data；
(3) pretreatment of data；
(4) modeling and analysis of data；
(5) optimize inservice inspection.
2. according to the method described in claim 1, it is characterized by: the data of collection include device identification number in step (1)
According to, sizing of equipment data, device type data, inservice inspection data, historical failure data, maintenance experience data, local environment
Data.
3. according to the method described in claim 1, it is characterized by: the data of collection include that equipment is uniquely compiled in step (1)
Code, device name, place system designator code, functions of the equipments, security level, specification grade, seismic behavior, quality guarantee grade, institute are in place
Set, manufacturing firm, inservice inspection method, inservice inspection frequency, acceptance criteria, last inservice inspection result, requirement for major repairs, on
Overhaul result, preventative maintenance require, last preventative maintenance result, operation troubles and equipment are born pressure,
Temperature, load information, it is some device-dependent including the pressure of equipment present position, temperature, humidity atmosphere
Information.
4. according to the method described in claim 1, it is characterized by: in step (2), based on current inservice inspection outline,
In conjunction with nuclear power plant's preventative maintenance, running equipment failure and overhaul mantenance data, inservice inspection integrated database is established.
5. according to the method described in claim 1, it is characterized by: in step (2), to establishing tables of data different in database
Sort merge is carried out, multilist connection is established.
6. according to the method described in claim 1, it is characterized by: in step (3), to duplicate, vacancy or abnormal
Data are handled, and are allowed to meet the requirements.
7. according to the method described in claim 1, it is characterized by: retrieving event once occurred in the database in step (4)
The equipment of barrier, using regression analysis, the case where finding out the feature and inservice inspection for being easy to appear failure, and pass through data and dig
Pick, finds out the data for the equipment that breaks down and the correlation of other data.
8. according to the method described in claim 7, it is characterized by: in step (4), in combination with equipment dependability database with
And nuclear power plant PSA analyzes data, more effectively to find the problem.
9. according to the method described in claim 7, it is characterized by: data for the equipment that breaks down, right in step (5)
Equipment with identical data increases the project and frequency of inservice inspection.
10. according to the method described in claim 1, it is characterized by: in step (5), according to the analysis of step (4) as a result, right
It is more in inservice inspection and be not easy the equipment to break down, it is proposed that reduce inservice inspection；It is less for inservice inspection and often send out
The equipment of raw failure, it is proposed that increase inservice inspection.
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| CN110414736A (en) * | 2019-07-30 | 2019-11-05 | 浙江长元科技有限公司 | A kind of wisdom fire-fighting safety predicting method and system based on Internet of Things |
| CN111340372A (en) * | 2020-02-27 | 2020-06-26 | 岭东核电有限公司 | Maintenance method and system for preventive production activity outline of nuclear power station |
| CN116542036A (en) * | 2023-04-26 | 2023-08-04 | 阳江核电有限公司 | Method and device for calculating in-service inspection implementation interval of nuclear power plant |
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| CN111340372A (en) * | 2020-02-27 | 2020-06-26 | 岭东核电有限公司 | Maintenance method and system for preventive production activity outline of nuclear power station |
| CN111340372B (en) * | 2020-02-27 | 2023-08-29 | 岭东核电有限公司 | Maintenance method and system for preventive production activity outline of nuclear power plant |
| CN116542036A (en) * | 2023-04-26 | 2023-08-04 | 阳江核电有限公司 | Method and device for calculating in-service inspection implementation interval of nuclear power plant |
| CN116542036B (en) * | 2023-04-26 | 2024-03-22 | 阳江核电有限公司 | Method and device for calculating in-service inspection implementation interval of nuclear power plant |
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